Modern medical diagnostics rely to a significant extent on medical imaging which, for example, is based on radiological, angiographic, sonographic and/or tomographic image records. Here, attempts are increasingly made to automatically identify and capture anatomical features in medical image records by the use of image analysis methods. Such a capture of anatomical features is often also referred to as registration.
The automatic capture of anatomical features in medical image records is generally made more difficult by virtue of a patient or a body part generally not assuming exactly the same position in various image records and elastic tissue elastically deforming to a different extent in the records, depending on the position of the patient. This applies, in particular, when comparing patient image records with reference image records, which often originate from different patients.
In this context, the publication “Geometry-Aware Multiscale Image Registration via OBBTree-Based Polyaffine Log-Demons” by C. Seiler, X. Pennec and M. Reyes in MICCAI'2011, Vol. 6892 of LNCS, Springer, 2011, pages 631 to 638, has disclosed the practice of deforming an image record depending on tissue stiffness in order to compensate for elastic deformations. However, this process requires specification on the part of the user to the extent of which tissue structures are substantially rigid and which are flexible.